US20240077605A1 - Change detection device and change detection method - Google Patents

Change detection device and change detection method Download PDF

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US20240077605A1
US20240077605A1 US18/280,384 US202118280384A US2024077605A1 US 20240077605 A1 US20240077605 A1 US 20240077605A1 US 202118280384 A US202118280384 A US 202118280384A US 2024077605 A1 US2024077605 A1 US 2024077605A1
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change detection
sar
coherence
image
dimensional structure
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Yuki Yamaguchi
Taichi Tanaka
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NEC Corp
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NEC Corp
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9021—SAR image post-processing techniques
    • G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9021—SAR image post-processing techniques

Definitions

  • This invention relates to a change detection device and a change detection method that performs change detection based on SAR images.
  • Synthetic aperture radar (SAR) technology is a technology which can acquire an image (hereinafter referred to as a SAR image) equivalent to the image by an antenna having a large aperture, when a radar mounted on a flying object such as an artificial satellite, an aircraft, or the like transmits and receives a radio wave while the flying object moves.
  • the synthetic aperture radar is utilized, for example, for analyzing a ground surface deformation by signal processing of reflected waves from the ground surface, etc.
  • an image taken by a flying object such as a satellite is called an observation image.
  • an observation image corresponds to a SAR image.
  • a flying object that transmits and receives electromagnetic waves is assumed to be a satellite, but a flying object is not limited to a satellite.
  • the coherence is calculated by complex correlation of pixels at the same position in multiple SAR images among K (K ⁇ 2) SAR images.
  • (p, q) is a pair of SAR images and c p, q are components of the coherence matrix.
  • Respective p and q are less than or equal to K and indicate one of the K SAR images.
  • the phase ⁇ p, q (specifically, the phase difference) is calculated for each pair of SAR images.
  • an absolute value of the value acquired by averaging exp( ⁇ j ⁇ p, q ) for a plurality of pixels in a predetermined area including pixels for coherence calculation is the component c p, q of the coherence matrix.
  • a p ⁇ A q ⁇ exp( ⁇ j ⁇ p, q ) may be averaged, where intensity in SAR image p is as A p and intensity in SAR image q is as A q .
  • the values represented by components of a coherence matrix are coherence values.
  • a coherence image in which the coherence values are pixel values is supposed.
  • a change detection device that uses a change detection technique that utilizes coherence performs change detection based on a coherence image.
  • the change detection device determines that a change has occurred when it detects an area with a low coherence value in the coherence image.
  • the change detection device generates a coherence image from a SAR image that has already been acquired and a new SAR image targeting the same area of observation as when the SAR image was acquired.
  • a change occurs in an area when a new structure appears or an existing structure disappears.
  • SAR images that have already been acquired are referred to as stored SAR images.
  • Newly acquired SAR images are sometimes referred to as SAR images to be compared.
  • Multiple SAR images are sometimes referred to as a group of SAR images.
  • a group of SAR images that has already been acquired consists of multiple SAR images that have already been acquired.
  • SAR images can be affected by layover. For example, in urban areas where structures exist in the observed area, reflected waves from tall and low structures and from the ground surface are mixed in the radar mounted on a satellite. As a result, the received waveform of the radar mounted on the satellite becomes unstable. Specifically, in a SAR image, layover of overlaying information of tall structures on information of low structures may occur. In a situation where layover occurs, changes may occur among multiple SAR images even if no changes actually occur in the observed area.
  • the coherence value decreases in the coherence image because the similarity between the SAR images decreases. In such a case, the sensitivity of change detection using coherence is reduced. For example, even if there is no actual change in the observed area, it may be misidentified as a change.
  • the applicable device generates three-dimensional information to reduce influence of layover from the multiple SAR images before the change (before the change occurs in the observed area).
  • the applicable device also generates three-dimensional information to reduce influence of layover from the multiple newly acquired SAR images. Then, the applicable device performs change detection by referring to both three-dimensional information.
  • multiple SAR images are needed multiple newly acquired SAR images after the change, as well as multiple SAR images before the change.
  • a large number of SAR images are needed to reduce influence of layover.
  • the applicable device performs processing to generate three-dimensional information using multiple SAR images before the change and processing to generate three-dimensional information using multiple newly acquired SAR images after the change. Therefore, many image acquisitions are required to reconstruct the three-dimensional structure before and after the change. Accordingly, image acquisition requires great care and time.
  • the change detection device includes three-dimensional structure reconstruction means for reconstructing a three-dimensional structure of a predetermined area in an observed area, phase elimination means for eliminating phase signals in the predetermined area in multiple SAR images in which the observed area is taken, using the three-dimensional structure, and change detection means for generating a coherence image from a SAR image pair from which the phase signals are eliminated and detecting change in the observed area based on coherence values of pixels constituting the coherence image.
  • the change detection method includes reconstructing a three-dimensional structure of a predetermined area in an observed area, eliminating phase signals in the predetermined area in multiple SAR images in which the observed area is taken, using the three-dimensional structure, and generating a coherence image from a SAR image pair from which the phase signals are eliminated and detecting change in the observed area based on coherence values of pixels constituting the coherence image.
  • the change detection program causes the computer to execute a process of reconstructing a three-dimensional structure of a predetermined area in an observed area, a process of eliminating phase signals in the predetermined area in multiple SAR images in which the observed area is taken, using the three-dimensional structure, and a process of generating a coherence image from a SAR image pair from which the phase signals are eliminated and detecting change in the observed area based on coherence values of pixels constituting the coherence image.
  • change detection can be performed with reduced influence of layover without reconstructing a three-dimensional structure after the change.
  • FIG. 1 It depicts a block diagram showing a configuration example of the change detection device of the first example embodiment.
  • FIG. 2 It depicts a flowchart showing an example of an operation of the change detection device of the first example embodiment.
  • FIG. 3 It depicts an explanatory diagram for explaining SAR tomography.
  • FIG. 4 It depicts a flowchart showing the three-dimensional structure reconstruction process in the first example embodiment.
  • FIG. 5 It depicts a flowchart showing the phase signal elimination process.
  • FIG. 6 It depicts a flowchart showing the coherent change detection process.
  • FIG. 7 It depicts a block diagram showing a configuration example of the change detection device of the second example embodiment.
  • FIG. 8 It depicts a flowchart showing an operation of the change detection device in the second example embodiment.
  • FIG. 9 It depicts a flowchart showing the three-dimensional structure reconstruction process in the second example embodiment.
  • FIG. 10 It depicts a block diagram showing a configuration example of the change detection device of the third example embodiment.
  • FIG. 11 It depicts a flowchart showing an operation of the change detection device in the third example embodiment.
  • FIG. 12 It depicts a block diagram showing a modification of the change detection device of the third example embodiment.
  • FIG. 13 It depicts a flowchart showing an operation of a modification of the change detection device in the third example embodiment.
  • FIG. 14 It depicts a block diagram showing a configuration example of the change detection device of the fourth example embodiment.
  • FIG. 15 It depicts a block diagram showing an example of a computer having a CPU.
  • FIG. 16 It depicts a block diagram showing the main part of the change detection device.
  • FIG. 17 It depicts a block diagram showing the main part of another change detection device.
  • FIG. 18 It depicts a block diagram showing the main part of still another change detection device.
  • FIG. 1 is a block diagram showing a configuration example of the change detection device of the first example embodiment.
  • the change detection device 100 shown in FIG. 1 comprises a three-dimensional structure reconstruction unit 110 , a phase eliminator 120 , and a coherent change detection unit 130 .
  • the three-dimensional structure reconstruction unit 110 reconstructs a three-dimensional structure of the observed area from multiple SAR images stored in the SAR image storage 700 .
  • the phase eliminator 120 includes a phase signal estimator 121 and a phase signal eliminator 122 .
  • the phase signal estimator 121 estimates a phase signal in a predetermined area in the observed area from the SAR image pair.
  • the predefined area is an area where layover may occur (layover area).
  • the phase eliminator 120 eliminates phase signals in the layover area.
  • the phase eliminator 120 refers to the three-dimensional structure of the observed area and eliminates phase signals caused by the height (height of the structure) that causes the layover.
  • the phase eliminator 120 uses three-dimensional point cloud data with information on intensity and phase reconstructed by SAR tomography to simulate signal mixing in the layover area. In other words, the phase eliminator 120 predicts phases that are not related to changes in the ground surface (i.e., phases caused by the height of structures). The phase eliminator 120 then eliminates signals with such phases from the observed signals.
  • phase signal due to height is considered to be highly variable among multiple SAR images. Therefore, elimination of a phase signal due to height reduces the change between multiple SAR images when no change actually occurs. As a result, more accurate coherent change detection can be performed even in the layover area.
  • the coherent change detection unit 130 generates a coherence image from one of the SAR images stored in the SAR image storage 700 and the SAR image to be compared.
  • the coherent change detection unit 130 uses the coherence image to determine whether a change has occurred in the observed area.
  • the SAR image to be compared may be a newly acquired SAR image or a SAR image selected from multiple SAR images stored in the SAR image storage 700 .
  • the three-dimensional structure reconstruction unit 110 reads a group of existing SAR images from the SAR image storage 700 . Then, the three-dimensional structure reconstruction unit 110 reconstructs the three-dimensional structure of a predetermined area in the observed area using a SAR tomography technique (step S 101 ).
  • the phase signal estimator 121 reads one SAR image from the SAR image storage 700 .
  • the phase signal estimator 121 also inputs the SAR image to be compared.
  • the phase signal estimator 121 estimates a phase signal of the SAR image pair of the SAR image read from the SAR image storage 700 and the SAR image to be compared in the layover area, utilizing the three-dimensional structure (step S 102 ).
  • the phase signal eliminator 122 eliminates the phase signal of the SAR image pair estimated by the phase signal estimator 121 (step S 103 ).
  • the coherent change detection unit 130 calculates a coherence value between the SAR images in the SAR image pair.
  • the coherent change detection unit 130 generates a coherence image with the coherence values as pixel values.
  • the coherent change detection unit 130 performs the coherent change detection process (step S 104 ). That is, the coherent change detection unit 130 determines whether or not there is an area in the observed area where a change has occurred.
  • the three-dimensional structure reconstruction unit 110 reconstructs the three-dimensional structure of a predetermined area in a three-dimensional structure reconstruction process using a SAR tomography technique.
  • FIG. 3 is an explanatory diagram for explaining SAR tomography.
  • the satellite travels in the vertical direction to the sheet. That is, the azimuth direction is the vertical direction to the sheet.
  • the satellite acquires SAR images of a predetermined observed area.
  • r indicates the range direction.
  • s indicates the elevation direction.
  • N corresponds to the number of SAR images stored in the SAR image storage 700 .
  • T denotes transposition.
  • the three-dimensional structure reconstruction unit 110 can estimate (calculate) the complex reflectivity distribution ⁇ at each position in the elevation direction from the observed values g and the steering matrix R.
  • the complex reflectivity distribution ⁇ includes intensity information and phase information. Therefore, the three-dimensional structure reconstruction unit 110 can acquire three-dimensional point cloud data representing the three-dimensional structure by estimating the complex reflectivity distribution ⁇ at each pixel.
  • the three-dimensional point cloud data is data of each point in the three-dimensional coordinates.
  • the bottom row in FIG. 3 shows an example of intensity distribution.
  • the intensity of reflected waves from a low-rise house is higher than the intensity of reflected waves from the ground surface (ground).
  • the intensity of reflected waves from a high-rise structure is higher.
  • FIG. 4 is a flowchart showing the three-dimensional structure reconstruction process performed by the three-dimensional structure reconstruction unit 110 .
  • FIG. 5 is a flowchart showing the phase signal elimination process performed by the phase eliminator 120 .
  • the phase signal estimator 121 in the phase eliminator 120 reads an existing SAR image from the SAR image storage 700 .
  • the phase signal estimator 121 also inputs a SAR image to be compared.
  • the phase signal estimator 121 interferes with the existing SAR image and the SAR image to be compared for each pixel of the SAR image, and estimates (calculates) a phase-to-elevation conversion coefficient for converting the phase included in each pixel after the interference into height (step S 121 ).
  • the phase signal estimator 121 estimates (calculates) the steering matrix Rail based on the phase-to-elevation conversion coefficient for each pixel (step S 122 ).
  • Ran shows the steering matrix for each point based on all existing SAR images and SAR image to be compared data.
  • the phase signal estimator 121 estimates (calculates) a received signal model g model for each pixel of the SAR image from the complex reflectivity distribution ⁇ and the steering matrix R all (step S 123 ).
  • the received signal model g model inferred from the three-dimensional structure, i.e., predicted observed values is in the layover area.
  • the phase signal eliminator 122 in the phase eliminator 120 generates observed signals (observed values, i.e., pixel values of the SAR image) g obs (step S 124 ).
  • the observed values g obs are the observed signals of the existing SAR image and the observed signals of the SAR image to be compared, respectively.
  • the phase signal eliminator 122 eliminates the phase signal predicted from the received signal model g model from the observed values g obs , for each pixel of the SAR image, as expressed in equation (2) (step S 125 ).
  • the phase eliminator 120 outputs a SAR image pair with the phase eliminated in a predetermined area to the coherent change detection unit 130 .
  • FIG. 6 is a flowchart showing the coherent change detection process performed by the coherent change detection unit 130 .
  • the coherent change detection unit 130 calculates coherence values between the SAR images of the SAR image pairs from the phase eliminator 120 (step S 131 ). In other words, the coherent change detection unit 130 generates a coherence image with the coherence values as pixel values.
  • the coherent change detection unit 130 determines whether there is a portion in the observed area where the coherence value is smaller than, for example, a predetermined threshold value (step S 132 ). When such a portion exists, the coherent change detection unit 130 determines that a change has occurred in the observed area (step S 133 ). When no such portion exists, the coherent change detection unit 130 determines that no change has occurred in the observed area (step S 134 ).
  • the coherent change detection unit 130 determines that a change has occurred in the observed area when the values (coherence values) of all pixels in an area (portion) of a predetermined size in the coherence image are smaller than a predetermined threshold value.
  • the coherent change detection unit 130 may determine that a change has occurred in the observed area when there are more than a predetermined percentage of pixels, whose coherence values are smaller than a predetermined threshold value, in an area of a predetermined size.
  • the three-dimensional structure reconstruction unit 110 reconstructs the three-dimensional structure of the layover area using a SAR tomography technique.
  • the phase eliminator 120 estimates the received signal model g model from the three-dimensional structure.
  • the phase eliminator 120 then eliminates the phase predicted from the received signal model g model from the observed signals.
  • the phase to be eliminated is, for example, the phase due to the height of the structure. Since the height of the structure is a cause of layover, the observed signals from which the phase is eliminated are signals from which influence of the layover is excluded.
  • the coherent change detection unit 130 can perform a coherent change detection process based on the observation signals from which the phase due to the height of the structure has been eliminated. In other words, the coherent change detection unit 130 can perform a coherent change detection process in which influence of the layover is excluded. In addition, the coherent change detection unit 130 can perform a coherent change detection process with high accuracy in the layover area.
  • the change detection device 100 does not require great care for acquiring a sufficient number of SAR images to reconstruct a three-dimensional structure after the change, compared to the process of generating three-dimensional information using multiple SAR images before the change and multiple newly acquired SAR images after the change. That is because the change detection device 100 does not require a process of generating three-dimensional information using multiple SAR images to be compared.
  • phase signal elimination can be performed more precisely than when using DEM. That is because the phase signals can be estimated for each structure such as a building when the three-dimensional structure is reconstructed using SAR tomography, while only phase information regarding large structures is reflected in the three-dimensional when using DEM.
  • phase signal estimation is possible even if the structures are complexly distributed in the observed area.
  • a received signal model is generated that is closer to the actual three-dimensional structure than when a three-dimensional structure is reconstructed using DEM. That is because when using SAR tomography, three-dimensional point cloud data with intensity and phase information is generated.
  • reconstruction of a three-dimensional structure by using SAR tomography has the advantage that a received signal model that is closer to the actual three-dimensional structure can be generated, as compared with reconstruction of a three-dimensional structure by using LiDAR (Light Detection and Ranging).
  • FIG. 7 is a block diagram showing a configuration example of the change detection device of the second example embodiment.
  • the change detection device 200 shown in FIG. 7 comprises a three-dimensional structure reconstruction unit 110 , a phase eliminator 220 , and a coherent change detection unit 230 .
  • the configuration and operation of the three-dimensional structure reconstruction unit 110 are the same as those in the first example embodiment.
  • the SAR image storage 700 stores, for example, respective SAR images for one observed area acquired in each orbit (path) among multiple orbits (multipath) of the satellite that are displaced from each other.
  • the phase eliminator 220 inputs multiple SAR images acquired in multiple orbits.
  • the phase eliminator 220 includes a phase signal estimator 221 and a phase signal eliminator 222 .
  • the phase signal estimator 221 inputs a group of SAR images including multiple SAR images stored in the SAR image storage 700 and one or more SAR images to be compared.
  • the one or more SAR images to be compared may all be newly acquired SAR images, or may include both SAR images selected from the multiple SAR images stored in the SAR image storage 700 and newly acquired SAR images.
  • the phase signal estimator 221 estimates the phase signals in a predetermined area (layover area) of all the SAR images constituting a group of SAR images.
  • the phase eliminator 220 eliminates phase signals in the layover area of all SAR images.
  • the coherent change detection unit 230 generates coherence images for all SAR image pairs.
  • the three-dimensional structure reconstruction unit 110 operates in the same manner as in the first example embodiment to reconstruct the three-dimensional structure of a predetermined area in the observed area (step S 101 ).
  • the phase signal estimator 221 estimates phase signals in a predetermined area (layover area) of all SAR images with reference to the three-dimensional structure (step S 202 ).
  • the phase signal eliminator 222 eliminates the phase signals estimated by the phase signal estimator 221 for all SAR images (step S 203 ).
  • the specific method of phase signal estimation and elimination is the same as the method in the first example embodiment (refer to FIG. 5 , etc.).
  • the phase eliminator 220 outputs all SAR images from which the phase of the predetermined area has been eliminated to the coherent change detection unit 230 .
  • the coherent change detection unit 230 performs the coherent change detection process (step S 204 ). That is, the coherent change detection unit 130 determines whether a change has occurred in the observed area.
  • FIG. 9 is a flowchart showing the coherent change detection process performed by the coherent change detection unit 230 .
  • the coherent change detection unit 230 calculates coherence values of all combinations (pairs) of SAR images in a group of SAR images (multiple SAR images stored in the SAR image storage 700 and one or more SAR images to be compared are included) (step S 230 ).
  • the coherent change detection unit 230 also calculates a typical coherence value for determining whether a change has occurred in the observed area (step S 231 ).
  • the typical coherence value corresponds to a coherence value between SAR images of a SAR image pair with no change or a change smaller than a predetermined acceptable value.
  • the coherent change detection unit 230 arranges the calculated coherence values for all SAR image pairs in a two-dimensional array, for example, to acquire the typical coherence values. In other words, the coherent change detection unit 230 generates a coherence matrix with the calculated coherence values as elements.
  • the horizontal axis of the two-dimensional array corresponds to the image number of one SAR image in all SAR image pairs.
  • the vertical axis of the two-dimensional array corresponds to the image number of the other SAR image in all SAR image pairs.
  • the coherent change detection unit 230 takes, for example, the largest coherence value in a two-dimensional array as the typical coherence value.
  • the coherent change detection unit 230 compares the coherence values between SAR images of all SAR image pairs with the typical coherence value. When there are multiple SAR image pairs that present coherence values that are greatly different from the typical coherence values, the coherent change detection unit 230 determines that a change has occurred in the observed area (step S 233 ). When there are no such SAR image pairs, the coherent change detection unit 230 determines that no change has occurred in the observed area (step S 234 ).
  • the “difference” in the coherence value with a great difference from the typical coherence value is a pre-defined value.
  • the “multiple” in the case of multiple SAR images with a great difference in coherence value is a pre-defined value.
  • use of multiple SAR images acquired in a multipath in coherent change detection has the effect of improving the robustness of coherent change detection in addition to the effect of the first example embodiment.
  • the acquisition times of SAR images acquired in each pass in a multipath are different. Therefore, when a group of SAR images includes multiple SAR images to be compared, it is possible to recognize when a change occurred in the observed area based on the acquisition time of the SAR image to be compared in the SAR image pair that presents a coherence value with a great difference from the typical coherence value.
  • FIG. 10 is a block diagram showing an example configuration of the change detection device of the third example embodiment.
  • the change detection device 300 shown in FIG. 10 comprises a three-dimensional structure reconstruction unit 110 , a phase eliminator 320 , and a coherent change detection unit 230 .
  • the configuration and operation of the three-dimensional structure reconstruction unit 110 are the same as those in the first and second example embodiments.
  • the configuration and operation of the coherent change detection unit 230 are the same as those in the second example embodiment.
  • the phase eliminator 320 includes a phase signal estimator 221 , a pixel identification unit 321 , and a phase signal eliminator 223 .
  • the configuration and operation of the phase signal estimator 221 are the same as those in the second example embodiment. That is, the phase signal estimator 221 inputs a group of SAR images including multiple SAR images stored in the SAR image storage 700 and one or more SAR images to be compared.
  • the phase signal estimator 221 estimates phase signals in a predetermined area (layover area) for all SAR images comprising the group of SAR images.
  • the phase signal eliminator 223 eliminates phase signals of the pixels identified by the pixel identification unit 321 for all SAR images.
  • the pixel identification unit 321 identifies pixels in each SAR image from which phase signals should be eliminated.
  • the three-dimensional structure reconstruction unit 110 operates as in the first and second example embodiments to reconstruct a three-dimensional structure of a predetermined area in the observed area (step S 101 ).
  • the phase signal estimator 221 operates as in the first and second example embodiments to estimate phase signals in the predetermined area for all SAR images (step S 202 ).
  • the pixel identification unit 321 calculates average intensity (each of average intensities of pixels at the same location in multiple SAR images) of each pixel in the SAR image over all SAR images (step S 301 ).
  • the pixel identification unit 321 identifies the pixel as a pixel from which the phase signal should be eliminated (step S 302 ). In that case, the process moves to step S 203 A. When the average intensity of the pixel is less than or equal to the predetermined value, the process moves to step S 204 . In step S 302 , the pixel identification unit 321 targets all SAR images, therefore compares the intensity of each pixel in each SAR image with the average intensity of the pixel.
  • a predetermined value a threshold for filtering of pixel selection
  • the pixel identification unit 321 identifies the pixel in the SAR image (SAR image whose pixels are subject to the comparison process with the average intensity among all SAR images) as the pixel from which the phase signal is to be eliminated.
  • step S 203 A the phase signal eliminator 222 eliminates the phase signals of the pixels identified by the pixel identification unit 321 for all SAR images.
  • the specific method of phase signal estimation and elimination is the same as the method in the first example embodiment (refer to FIG. 5 , etc.). However, in this example embodiment, the phase signal eliminator 222 eliminates the phase predicted from the received signal model g model from the pixel identified by the pixel identification unit 321 in the observation signal. Then, the process moves to step S 204 .
  • step S 204 the coherent change detection unit 230 performs the coherent change detection process as in the second example embodiment.
  • the phase signal of the pixel in the SAR image is eliminated.
  • pixels with low intensity are not subject to phase signal elimination.
  • the reliability of phase information for pixels with low intensity may be low. If the coherent change detection process is performed after the phase signal elimination process is applied to such pixels, there is rather a risk of false detection of coherent change.
  • the phase signal elimination process is not applied to pixels with low intensity, as in this example embodiment, the possibility of false detection of coherent change is expected to be reduced.
  • FIG. 12 is a block diagram showing a modification of the change detection device of the third example embodiment.
  • the change detection device 310 shown in FIG. 12 comprises a three-dimensional structure reconstruction unit 110 , a phase eliminator 330 , and a coherent change detection unit 230 .
  • the phase eliminator 330 includes a pixel identification unit 321 , a phase signal estimator 221 , and a phase signal eliminator 222 .
  • the pixel identification unit 321 operates before the phase signal is estimated.
  • the configuration and operation of the three-dimensional structure reconstruction unit 110 are the same as those in the first to third example embodiments.
  • the configuration and operation of the coherent change detection unit 230 are the same as those in the second and third example embodiments.
  • the pixel identification unit 321 calculates average intensity (each of average intensities of pixels at the same location in multiple SAR images) of each pixel in the SAR image over all SAR images (step S 301 ).
  • step S 101 When the average intensity of the pixels is greater than a predetermined value (threshold for filtering pixel selection), the process moves to step S 101 (step S 302 ). When the average intensity of the pixel is less than or equal to the predetermined value, the process moves to step S 204 .
  • step S 302 the pixel identification unit 321 targets all SAR images and compares the intensity of each pixel in each SAR image with the average intensity of the pixel in question. When the pixel identification unit 321 determines that the intensity of the pixel is greater than the average intensity of the pixel in question, the process moves to step S 101 . Otherwise, steps S 101 , S 202 , and S 203 are skipped.
  • steps S 101 , S 202 , and S 203 are the same as those in the second example embodiment. That is, the three-dimensional structure reconstruction unit 110 operates in the same manner as in the second example embodiment to reconstruct a three-dimensional structure of a predetermined area in the observed area (step S 101 ).
  • the phase signal estimator 221 estimates the phase signals in the predetermined area of all SAR images by referring to the three-dimensional structure, as in the second example embodiment (step S 202 ).
  • the phase signal eliminator 222 eliminates the phase signals estimated by the phase signal estimator 221 for all SAR images, as in the second example embodiment (step S 203 ).
  • the coherent change detection unit 230 performs the coherent change detection process as in the second example embodiment (step S 204 ).
  • the process of estimating the phase signal (step S 202 ) and the process of the eliminating the phase signal (step S 203 ) using the three-dimensional structure is executed when the average intensity of the pixel is greater than a predetermined value.
  • the process of estimating the phase signal and the process of the eliminating the phase signal are not executed for pixels with low intensity.
  • the reliability of phase information for pixels with low intensity may be low. If the coherent change detection process is performed after the phase signal elimination process is applied to such pixels, there is rather a risk of false detection of coherent change.
  • the process of estimating the phase signal and the phase signal elimination process are not applied to pixels with low intensity, as in this example embodiment, the possibility of false detection of coherent change is expected to be reduced.
  • the change detection devices 300 , 310 of above third example embodiment and its modification are configured by applying the pixel identification unit 321 to the change detection device 200 of the second example embodiment.
  • the pixel identification unit 321 may be applied to the change detection device 100 of the first example embodiment.
  • the three-dimensional structure reconstruction unit 110 acquires three-dimensional point cloud data representing the three-dimensional structure using a SAR tomography technique which uses multiple SAR images stored in the SAR image storage 700 so as to reconstruct the three-dimensional structure of a predetermined area in the observed area.
  • the three-dimensional point cloud data may be acquired without using a SAR tomography technique.
  • the change detection device uses other kinds of three-dimensional data, not three-dimensional point cloud data based on SAR images, to reconstruct a three-dimensional structure of a predetermined area.
  • Such three-dimensional data include, for example, three-dimensional point cloud data acquired by LiDAR, a digital surface model (DSM), data including three-dimensional information (for example, polygon data of a structure, etc.) generated from images acquired by an optical satellite, etc.
  • DSM digital surface model
  • the following is an example where a change detection device uses data acquired by LiDAR, but 3D imaging devices other than LiDAR can also be used.
  • FIG. 14 is a block diagram showing a configuration example of the change detection device of the fourth example embodiment.
  • the change detection device 400 shown in FIG. 14 comprises a three-dimensional structure reconstruction unit 111 , a phase eliminator 120 , and a coherent change detection unit 130 .
  • the LiDAR data storage 800 stores three-dimensional point cloud information (three-dimensional point cloud data) that includes intensity of each point in the observed area, in advance.
  • the information (data) including intensity is three-dimensional point group data based on the analysis result of reflected light from the observed area received by general 3D (dimension) LiDAR.
  • the three-dimensional structure reconstruction unit 111 estimates three-dimensional point cloud data in the SAR image from the three-dimensional point cloud data stored in the LiDAR data storage 800 .
  • the three-dimensional structure reconstruction unit 111 estimates three-dimensional point cloud data in the SAR image based on a simulation for a satellite acquiring SAR images.
  • a simulation procedure for a satellite acquiring SAR images includes a method of inputting a DSM generated from the three-dimensional point cloud data stored in the LiDAR data storage 800 , transforming it to the SAR coordinate system (azimuth-range coordinates), estimating positions of single scattering, twice scattering, three times scattering, and radar shadow based on a shape of the DSM and position information of the satellite, and estimating intensity and a phase considering a reflection coefficient and roughness of the reflective surface.
  • the three-dimensional point cloud data stored in the LiDAR data storage 800 is substantially converted to three-dimensional point cloud data in the SAR image by the three-dimensional structure reconstruction unit 111 .
  • phase eliminator 120 and the coherent change detection unit 130 operate similarly to those in the first example embodiment.
  • the change detection device 400 does not perform the process of reconstructing a three-dimensional structure by SAR tomography. Therefore, the change detection device 400 can reduce processing time compared to the change detection device 100 of the first example embodiment.
  • the change detection device 400 of this example embodiment is configured by applying the three-dimensional structure reconstruction unit 111 using three-dimensional point cloud data by LiDAR to the change detection device 100 of the first example embodiment.
  • the three-dimensional structure reconstruction unit 111 may be applied to the change detection device 200 of the second example embodiment, the change detection device 300 of the third example embodiment, or the change detection device 310 of the modification.
  • the change detection devices of each of the above example embodiments generates three-dimensional point cloud data by SAR tomography or other methods and eliminates phase components in a predetermined area (layover area) from the observation signal by using the three-dimensional point cloud data.
  • the sensitivity of change detection by such a change detection device does not reduce even in a case where layover occurs in the observed area.
  • the change detection device can also accurately detect coherent change in the layover area.
  • the change detection device does not need to perform a process of generating three-dimensional point cloud data related to the SAR image to be compared.
  • the change detection device can perform sensitive change detection even with only one SAR image to be compared. Therefore, it does not take care for collecting SAR images to be compared, and processing a load of the change detection device does not increase so much. As a result, the coherent change detection process can be performed in a short time.
  • the change detection device can perform the coherent change detection in a short period of time, the change detection device can detect a change quickly when the change detection device is used in an application of monitoring an observed area on a regular basis.
  • Each of the above embodiments can be configured in hardware, but can also be realized by a computer program. It is also possible to configure a part of components in each of the above example embodiments in hardware and the other part in software.
  • FIG. 15 is a block diagram showing an example of a computer having a CPU.
  • the computer is implemented in the change detection device of each of the above example embodiments.
  • the CPU 1000 executes processing in accordance with a change detection program (software component: codes) stored in a storage device 1001 to realize the functions in the above example embodiments. That is, the computer realizes the functions of the three-dimensional structure reconstruction units 110 , 111 , the phase eliminators 120 , 220 , 320 , 330 , and the coherent change detection units 130 , 230 in the change detection devices 100 , 200 , 300 , 310 , 400 shown in FIG. 1 , FIG. 7 , FIG. 10 , FIG. 12 , and FIG. 14 .
  • the storage device 1001 is, for example, a non-transitory computer readable media.
  • the non-transitory computer readable medium is one of various types of tangible storage media. Specific examples of the non-transitory computer readable media include a magnetic storage medium (for example, hard disk), a magneto-optical storage medium (for example, magneto-optical disk), a CD-ROM (Compact Disc-Read Only Memory), a CD-R (Compact Disc-Recordable), a CD-R/W (Compact Disc-ReWritable), and a semiconductor memory (for example, a mask ROM, a PROM (programmable ROM), an EPROM (Erasable PROM), a flash ROM).
  • a magnetic storage medium for example, hard disk
  • a magneto-optical storage medium for example, magneto-optical disk
  • CD-ROM Compact Disc-Read Only Memory
  • CD-R Compact Disc-Recordable
  • CD-R/W Compact Disc-ReWritable
  • the program may be stored in various types of transitory computer readable media.
  • the transitory computer readable medium is supplied with the program through, for example, a wired or wireless communication channel, i.e., through electric signals, optical signals, or electromagnetic waves.
  • a memory 1002 is a storage means implemented by a RAM (Random Access Memory), for example, and temporarily stores data when the CPU 1000 executes processing. It can be assumed that a program held in the storage device 1001 or a temporary computer readable medium is transferred to the memory 1002 and the CPU 1000 executes processing based on the program in the memory 1002 .
  • RAM Random Access Memory
  • FIG. 16 is a block diagram showing the main part of the change detection device.
  • the change detection device 10 shown in FIG. 16 comprises a three-dimensional structure reconstruction unit (three-dimensional structure reconstruction means) 11 (in the example embodiments, realized by the three-dimensional structure reconstruction units 110 , 111 ) which reconstructs a three-dimensional structure of a predetermined area (for example, a layover area) in an observed area, a phase eliminator (phase elimination means) 12 (in the example embodiments, realized by the phase eliminators 120 , 220 , 320 , 330 ) which eliminates phase signals in the predetermined area in multiple SAR images in which the observed area is taken, using the three-dimensional structure, and a change detection unit (change detection means) 13 (in the example embodiments, realized by the coherent change detection units 130 and 230 ) which generates a coherence image from a SAR image pair from which the phase signals are eliminated and detects change in the observed area based on coherence values of pixels constituting the coherence image.
  • FIG. 17 is a block diagram showing the main part of another change detection device.
  • the three-dimensional structure reconstruction unit 11 includes a three-dimensional point cloud data estimation unit 11 A (in the example embodiments, realized by the three-dimensional structure reconstruction unit 110 ) which estimates three-dimensional point cloud data including intensity and phase information using SAR tomography, as the three-dimensional structure.
  • FIG. 18 is a block diagram showing the main part of still another change detection device.
  • the three-dimensional structure reconstruction unit 11 includes a three-dimensional point cloud data conversion unit (three-dimensional point cloud data conversion means) 11 B (in the example embodiments, realized by the three-dimensional structure reconstruction unit 111 which executes a simulation related to SAR) for estimating three-dimensional point cloud data including intensity and phase information using data including three-dimensional information (as an example, three-dimensional point cloud data by LiDAR).
  • a change detection device comprising:

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